Követés
Suraj Srinivas
Suraj Srinivas
Research Scientist at Bosch
E-mail megerősítve itt: us.bosch.com - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Data-free parameter pruning for deep neural networks
S Srinivas, RV Babu
British Machine Vision Conference (BMVC), 2015
7112015
A taxonomy of deep convolutional neural nets for computer vision
S Srinivas, RK Sarvadevabhatla, KR Mopuri, N Prabhu, SSS Kruthiventi, ...
Frontiers in Robotics and AI 2, 172022, 2016
354*2016
Full-gradient representation for neural network visualization
S Srinivas, F Fleuret
Neural Information Processing Systems (NeurIPS), 2019
3372019
Training sparse neural networks
S Srinivas, A Subramanya, R Venkatesh Babu
CVPR Embedded Vision Workshop, 138-145, 2017
2512017
Knowledge Transfer with Jacobian Matching
S Srinivas, F Fleuret
International Conference on Machine Learning (ICML), 2018
2022018
Certifying llm safety against adversarial prompting
A Kumar, C Agarwal, S Srinivas, AJ Li, S Feizi, H Lakkaraju
arXiv preprint arXiv:2309.02705, 2023
1532023
Which explanation should i choose? a function approximation perspective to characterizing post hoc explanations
T Han, S Srinivas, H Lakkaraju
Neural Information Processing Systems (NeurIPS), 2022
972022
Estimating Confidence for Deep Neural Networks through Density modeling
A Subramanya, S Srinivas, RV Babu
2018 International Conference on Signal Processing and Communications (SPCOM …, 2018
68*2018
Rethinking the Role of Gradient Based Attribution Methods for Model Interpretability
S Srinivas, F Fleuret
International Conference on Learning Representations (ICLR), 2021
532021
Generalized dropout
S Srinivas, RV Babu
Tech Report, 2016
512016
Learning the architecture of deep neural networks
S Srinivas, RV Babu
British Machine Vision Conference (BMVC), 2016
48*2016
Efficient Training of Low-Curvature Neural Networks
S Srinivas, K Matoba, H Lakkaraju, F Fleuret
Neural Information Processing Systems (NeurIPS), 2022
232022
Interpreting clip with sparse linear concept embeddings (splice)
U Bhalla, A Oesterling, S Srinivas, FP Calmon, H Lakkaraju
arXiv preprint arXiv:2402.10376, 2024
222024
Data-efficient structured pruning via submodular optimization
M El Halabi, S Srinivas, S Lacoste-Julien
Neural Information Processing Systems (NeurIPS), 2022
202022
Cyclical Pruning for Sparse Neural Networks
S Srinivas, A Kuzmin, M Nagel, M van Baalen, A Skliar, T Blankevoort
CVPR Workshop on Efficient Deep Learning for Computer Vision, 2022
192022
Discriminative feature attributions: bridging post hoc explainability and inherent interpretability
U Bhalla, S Srinivas, H Lakkaraju
Advances in neural information processing systems 36, 44105-44122, 2023
14*2023
Which models have perceptually-aligned gradients? an explanation via off-manifold robustness
S Srinivas, S Bordt, H Lakkaraju
Advances in neural information processing systems 36, 21172-21195, 2023
132023
Compensating for large in-plane rotations in natural images
L Boominathan, S Srinivas, RV Babu
Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), 2016
72016
On Minimizing the impact of dataset shifts on actionable explanations
AP Meyer, D Ley, S Srinivas, H Lakkaraju
Uncertainty in Artificial Intelligence, 1434-1444, 2023
52023
Word-level explanations for analyzing bias in text-to-image models
A Lin, LM Paes, SH Tanneru, S Srinivas, H Lakkaraju
arXiv preprint arXiv:2306.05500, 2023
52023
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